Data Scientist (AI & Synthetic Intelligence) in London

Data Scientist (AI & Synthetic Intelligence) in London

London Full-Time 72000 - 88000 £ / year (est.) Home office (partial)
Cint

At a Glance

  • Tasks: Develop next-gen AI solutions and collaborate on innovative data science projects.
  • Company: Cint, a pioneer in research technology with a global presence.
  • Benefits: Competitive salary, growth opportunities, and a culture of collaboration and innovation.
  • Other info: Recognised as one of Newsweek's Top 100 Most Loved Workplaces.
  • Why this job: Join a dynamic team to shape the future of AI in market research.
  • Qualifications: 2-4 years in Data Science, strong skills in Python and machine learning.

The predicted salary is between 72000 - 88000 £ per year.

Who We Are

Cint is a pioneer in research technology (Res Tech).

Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more.

The Cint platform is built on a programmatic marketplace, which is the world's largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.

We are feeding the world's curiosity!

As a Data Scientist at Cint, you will play a pivotal role in developing next-generation AI solutions that power our product portfolio.

Collaborating closely with Product and Engineering teams, you will bridge the gap between traditional research data and synthetic intelligence.

You will focus on the research, validation, and delivery of models—including Large Language Models (LLMs)—that augment high-quality human signals across the Cint Exchange.

This role involves advanced data mining, robust data validation, and the development of sophisticated statistical and machine learning methodologies.

The ideal candidate can independently research, develop, and maintain high-impact solutions that align Cint's AI capabilities with market research trends, contributing to the technical roadmap for Cint's proprietary synthetic data platform.

Responsibilities

  • Contribute to the research, discovery, and development of machine learning models - specifically focused on synthetic row generation, open-ended text generation, and data augmentation.
  • Execute statistical tests and experiments to validate LLM performance and synthetic modeling hypotheses.
  • Develop logic for on-demand and dynamic boosting capabilities, collaborating with Engineering to integrate these models into Cint Exchange fielding workflows.
  • Design and refine sophisticated profiling taxonomies, leveraging large-scale datasets to create syndicated audiences.
  • Manage technical workflows and development cycles with guidance
  • Collaborate with Product and Engineering teams to support integration
  • Create clear, effective prototypes and deliverables that explain and defend complex Generative AI concepts to both technical and non-technical audiences.

Qualifications Required

  • Minimum 2-4 years of experience in a Data Science capacity, with experience delivering end-to-end data science solutions
  • A Master's degree (or equivalent) in Statistics, Data Science, or a related quantitative field.
  • Deep understanding of Generative AI and LLMs, particularly for applications in text generation and data synthesis.
  • Advanced knowledge of statistical techniques: hypothesis testing, sampling theory, experimental design, and causal inference.
  • Strong knowledge of a variety of ML techniques (e. g., clustering, regression, neural networks, etc.) and their real-world trade-offs.
  • Expert proficiency in Python (DS/ML stack) and experience with frameworks used for LLM development and fine-tuning.
  • Advanced SQL skills and experience working with large-scale databases.
  • Ability to research and adopt new methods

Essential Qualities

  • Highly accountable self-starter and quick learner, consistently motivated to deliver high-quality, impactful results.
  • Strong data-driven mindset with the ability to translate abstract business requests into actionable AI initiatives and solutions.
  • Excellent written and verbal communication skills, with the ability to communicate technical findings clearly

Nice to Have

  • Direct experience with Synthetic Data Generation techniques and the evaluation of synthetic data quality/utility.
  • Experience with Prompt Engineering, RAG (Retrieval-Augmented Generation), or fine-tuning open-source LLMs for open-end generation.
  • Experience with probabilistic modeling, or advanced profiling techniques.
  • Familiarity with online market research or survey exchange platforms.
  • Experience using Databricks, Spark, or Py Spark for large-scale workflows.

Our Values

  • Collaboration is our superpower
  • We uncover rich perspectives across the world
  • Success happens together
  • We deliver across borders.
  • Innovation is in our blood
  • We're pioneers in our industry
  • Our curiosity is insatiable
  • We bring the best ideas to life.
  • We do what we say
  • We're accountable for our work and actions
  • Excellence comes as standard
  • We're open, honest and kind, always.
  • We are caring
  • We learn from each other's experiences
  • Stop and listen; every opinion matters
  • We embrace diversity, equity and inclusion.
  • More About Cint

We're proud to be recognised in Newsweek's 2025 Global Top 100 Most Loved Workplaces, reflecting our commitment to a culture of trust, respect, and employee growth.

In June 2021, Cint acquired Berlin-based Gap Fish – the world's largest ISO certified online panel community in the DACH region – and in January 2022, completed the acquisition of US-based Lucid – a programmatic research technology platform that provides access to first-party survey data in over 110 countries.

Cint Group AB (publ), listed on Nasdaq Stockholm, this growth has made Cint a strong global platform with teams across its many global offices, including Stockholm, London, New York, New Orleans, Singapore, Tokyo and Sydney. (

Additionally, in a world of AI, we want our candidates to understand our approach to the use of AI during the interview and hiring process, so we'd appreciate you reading our AI usage guide.

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Data Scientist (AI & Synthetic Intelligence) in London employer: Cint

Cint is an exceptional employer that fosters a collaborative and innovative work culture, perfect for Data Scientists eager to make a significant impact in the media measurement space. With a strong emphasis on employee growth, Cint offers continuous learning opportunities and the chance to work with cutting-edge technologies in a vibrant location, ensuring that your contributions are valued and recognised. Join us to be part of a dynamic team where your expertise in data science will drive meaningful insights and solutions.

Cint

Contact Details:

Cint Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist (AI & Synthetic Intelligence) in London

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We think you need these skills to ace Data Scientist (AI & Synthetic Intelligence) in London

Data Science
Machine Learning
Generative AI
Large Language Models (LLMs)
Statistical Techniques
Hypothesis Testing
Python

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cint. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Cint

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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Get Comfortable with Python and R

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Prepare for Case Studies

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